Senior Machine Learning Engineer

Summary

Join Instacart as a Senior Machine Learning Engineer and contribute to redefining the in-store shopping experience using cutting-edge technology and AI. You will work on the core of our smart cart experience, designing and fine-tuning scalable models that integrate sensor data for effortless customer experiences. Collaborate with cross-functional teams to tackle complex challenges like object tracking and recognition, and help perfect our sensor ecosystem. This role involves building and improving core weight sensing models, developing robust sensor fusion models, improving signal quality, designing experiments, deploying models on edge devices, and creating infrastructure for sensor data management. The AI and Computer Vision team at Caper plays an integral role in Instacart’s mission, offering a diverse and collaborative environment.

Requirements

• Master’s or Ph.D. in Electrical and Computer Engineering (ECE), Computer Science, Applied Mathematics, or related fields
• Strong problem-solving, analytical, and experimental skills
• Excellent communication and presentation skills, with a track record of productive cross-functional collaboration
• Proficiency in programming languages such as Python, C++, or Java/Kotlin
• Strong experience with data science tools (e.g., SQL, Pandas) and machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
• Hands-on experience with embedded AI devices, notably the Nvidia Jetson platform

Responsibilities

• Build and improve core weight sensing models to enhance shopping cart accuracy and usability
• Develop robust sensor fusion models by integrating multiple sensor inputs
• Improve signal quality and ensure consistency across sensor data streams
• Design and execute experiments to generate actionable sensor data
• Deploy machine learning models on edge devices, such as the Nvidia Jetson platform
• Create infrastructure to collect, process, and store sensor data efficiently

Preferred Qualifications

• 3+ years of experience developing and deploying machine learning models and implementing sensor fusion in production environments
• Experience working with large language models (LLMs) or vision-language models (VLMs)
• Familiarity with A/B testing methodologies and experimentation in industrial environments
• Exposure to hardware product development, onboard edge computing, and signal processing challenges
• Strong track record of translating research into production while maintaining an iterative and fast-paced workflow
• Proactive self-starter with the ability to independently identify problems and drive solutions

Benefits

• Highly market-competitive compensation and benefits
• New hire equity grant
• Annual refresh grants